Recep Tayyip Erdoğan Üniversitesi Kurumsal Akademik Arşivi
DSpace@RTEÜ, Recep Tayyip Erdoğan Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
CPU-based parallelization of BDAC: Enhancing K-Clique approximation
(Springer, 2026) Ergenç Çalmaz, Büşra; Bostanoğlu, Belgin
The number of k-cliques in a dataset is significant and employed in diverse fields, including community detection, anomaly detection, and spam detection. This facilitates the identification of densely connected clusters or groups of nodes, which can subsequently be used to reveal underlying structures or patterns in the data. However, the combinatorial complexity of counting k-cliques, especially when identifying them in large networks or for higher values of k, poses considerable computational difficulties. This study introduces an accelerated version of the Boundary-Driven Approximations of K-Cliques (BDAC) algorithm, emphasizing CPU-based parallelization to boost performance when working with large, dense graphs. The BDAC algorithm sets a boundary for k-clique counts instead of providing a specific estimation, which removes the need for recursive enumeration and sampling. We evaluate the performance of BDAC on various graph datasets, showing clear improvements in execution time with parallelization while still keeping the approximation bounds intact. The results show that accelerated BDAC is particularly effective for dense networks, achieving efficient k-clique approximations at large scales. This work highlights the potential of BDAC for high-speed network analysis, contributing an optimized, scalable solution for k-clique approximation in complex datasets.
Unveiling key biomarkers of cardiovascular risk in psoriasis through explainable artificial intelligence
(Multidisciplinary Digital Publishing Institute (MDPI), 2026) Ucuzal, Hasan; Kıvrak, Mehmet
Psoriasis patients face a significantly elevated risk of cardiovascular diseases (CVD), necessitating early and accurate risk prediction tools. This study developed and validated a machine learning model to predict CVD risk in psoriasis patients using clinical and biochemical data from 2685 individuals. After preprocessing and addressing class imbalance with SMOTE-NC, six machine learning models (Logistic Regression as baseline, XGBoost, LightGBM, CatBoost, GradientBoosting, AdaBoost) were evaluated using a completely leak-free nested cross-validation framework (outer k = 10, inner k = 3) with randomized hyperparameter search (n_iter = 50). Feature selection via the Boruta algorithm was performed separately within each training fold to prevent data leakage. The Boruta algorithm identified 21 key predictors, including age, systolic blood pressure (SBP), apolipoprotein B (apoB), fasting blood glucose (FBG), and complement C1q. CatBoost emerged as the top-performing model (OOF ROC-AUC = 0.908, 95% CI [0.892–0.924]; PR-AUC = 0.509, 95% CI [0.448–0.578]; F1 = 0.540; MCC = 0.498; Brier = 0.078), while the Logistic Regression baseline achieved ROC-AUC = 0.909 but was eliminated due to poor calibration (Brier = 0.114 > 0.10). All metrics were evaluated with 95% bootstrap confidence intervals (n = 1000 iterations). Explainable AI techniques (SHAP, LIME, Anchors) revealed that older age, elevated SBP, and metabolic dysregulation (e.g., high apoB, FBG) were the strongest CVD predictors. Local explanations were provided for five representative patients (high-risk, low-risk, and randomly selected), rather than a single instance, to better characterize model stability. Limitations include the single-center, retrospective design and lack of external validation. Future work should incorporate multi-ethnic cohorts and advanced biomarkers (e.g., genetic, imaging data) to enhance generalizability. This study demonstrates the potential of explainable AI to improve CVD risk stratification in psoriasis patients, offering a scalable tool for preventive cardiology.
Comment on “Current status and comparative risk assessment of microplastic pollution in surface water and sediment from the Black Sea coastline using geospatial analysis” by Özpolatet al.(2026)
(Elsevier, 2026) Gündoğdu, Sedat; Gedik, Kenan; Terzi, Yahya; Öztürk, Rafet Çağrı
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Comparison of transobturator tape and functional electrical stimulation methods in pure stress urinary incontinence
(Elsevier, 2026) Doğan, Osman; Ural, Ülkü Mete; Tekin, Yeşim Bayoğlu; Şentürk, Şenol; Balık, Gülşah; Güven, Seda Güvendağ
Objective: The aim of the current study was to compare the effectiveness of the functional electrical stimulation (FES) and transobturator tape (TOT) methods in the management of pure stress urinary incontinence (SUI). Materials and methods: This clinical study was performed on 58 pure SUI patients. FES and TOT groups were compared in terms of intensity of complaints and changes in quality of life before and after the therapy. The ICIQ-SF and EORTC QLQ-30 questionnaires were applied via interview method. The objective cure rate was evaluated by cough and pad tests. Results: ICIQ-SF scores before and after the treatment and EORTC QLQ-30 scores before the treatment were similar in FES and TOT groups. After treatment, functional and symptomatic outcomes were similar in FES and TOT groups (p = 0.05 and p = 0.115), while general health status outcomes were better in FES group (p = 0.007). There was no significant difference between two groups regarding the objective cure rate. Conclusion: Our results have shown that FES and TOT are similar in their effect on the alleviation of urine leakage. However, FES seems to be superior to TOT for improvement of quality of life. Further studies are needed to compare the efficacy of these two treatment modalities.
Piezoelectrically actuated control of nonlinear vibrations and resonant instabilities in rotating cylindrical structures
(Elsevier, 2026) Owida, Hamza Abu; Mohammad, Suleiman Ibrahim; Vasudevan, Asokan; Mohammad, Anber Abraheem Shlash; Velavan, Geetha; Mabrouk, Abdelkader; Yaylacı, Murat
This research examines how to control axial vibrations using piezoelectric elements and their associated nonlinear vibrational behaviours with regard to rotating cylindrical shells. This will require the use of axial thermal loads in the design model, which utilises the following criteria: (1) As a thin-walled sandwich beam, it consists of a porous functional grading (FG) core and piezoelectric sensor and actuator layers. (2) A thin-walled Rayleigh beam formulation that incorporates geometric nonlinear effects of the von Kármán type to predict varying amplitude of vibration and impact of the piezoelectric elements. (3) The constitutive model of each piezoelectric element, which allows for active control through negative proportional displacement feedback, provides a method for controlling axial vibrations. (4) The governing equations of motion take into account the gyroscopic effects of the rotation and the influence of an interior fluid. The governing equations are derived using Hamilton's principle by retaining all terms up to cubic order and dropping all higher than cubic order terms for the purposes of being analytic. To accomplish this, the Galerkin method is used to convert the resulting partial differential equations (PDEs) into a series of ordinary differential equations (ODEs), and as a group of ODEs, allows the evaluation of a steady state or resonant response using a harmonic trial solution. Investigations into piezoelectric actuation as a means of reducing nonlinear resonant vibrations and preventing dynamic instability from occurring under combined loading conditions that produce thermal, rotational, and fluid loads have been thoroughly conducted. Several parametric analyses reveal how critical rotational speed, thermal gradients, feedback gains, and material gradation are to the conditions that result in the onset of resonant instability and amplitude modulation. The results obtained from these investigations indicate that properly tuned negative displacement proportional feedback can produce a considerable increase in dynamic stability, a reduction in the amplitude of vibration, and a delay of resonance when subjected to multiple types of loading. The results will therefore serve as a useful guideline for designing active vibration control systems for advanced rotating cylindrical systems utilizing multifunctional engineered material architectures.
